Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere A Thomas, S Clémençon, A Gramfort, A Sabourin Proceedings of the 20th International Conference on Artificial Intelligence …, 2017 | 22 | 2017 |
Mass volume curves and anomaly ranking S Clémençon, A Thomas Electronic Journal of Statistics 12 (2), 2806-2872, 2018 | 20 | 2018 |
Calibration of One-Class SVM for MV set estimation A Thomas, V Feuillard, A Gramfort Data Science and Advanced Analytics (DSAA), 2015. 36678 2015. IEEE …, 2015 | 20 | 2015 |
Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose? B Kégl, G Hurtado, A Thomas International Conference on Learning Representations, 2020 | 15 | 2020 |
Parallel Contextual Bandits in Wireless Handover Optimization I Colin, A Thomas, M Draief 2018 IEEE International Conference on Data Mining Workshops (ICDMW), 258-265, 2018 | 12 | 2018 |
Learning Hyperparameters for Unsupervised Anomaly Detection. A Thomas, S Clémençon, V Feuillard, A Gramfort | 12 | 2016 |
Best Arm Identification in Graphical Bilinear Bandits G Rizk, A Thomas, I Colin, R Laraki, Y Chevaleyre International Conference on Machine Learning, 9010-9019, 2021 | 9 | 2021 |
Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level A Grosnit, A Maraval, J Doran, G Paolo, A Thomas, RSHN Beevi, ... arXiv preprint arXiv:2411.03562, 2024 | 3 | 2024 |
Guided Safe Shooting: model based reinforcement learning with safety constraints G Paolo, J Gonzalez-Billandon, A Thomas, B Kégl arXiv preprint arXiv:2206.09743, 2022 | 3 | 2022 |
Refined bounds for randomized experimental design G Rizk, I Colin, A Thomas, M Draief arXiv preprint arXiv:2012.15726, 2020 | 3 | 2020 |
Multi-timestep models for Model-based Reinforcement Learning A Benechehab, G Paolo, A Thomas, M Filippone, B Kégl arXiv preprint arXiv:2310.05672, 2023 | 1 | 2023 |
Zero-shot Model-based Reinforcement Learning using Large Language Models A Benechehab, YAE Hili, A Odonnat, O Zekri, A Thomas, G Paolo, ... arXiv preprint arXiv:2410.11711, 2024 | | 2024 |
Differentially Private Model-Based Offline Reinforcement Learning A Rio, M Barlier, I Colin, A Thomas arXiv preprint arXiv:2402.05525, 2024 | | 2024 |
A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning A Benechehab, A Thomas, G Paolo, M Filippone, B Kégl arXiv preprint arXiv:2402.03146, 2024 | | 2024 |
Deep autoregressive density nets vs neural ensembles for model-based offline reinforcement learning A Benechehab, A Thomas, B Kégl arXiv preprint arXiv:2402.02858, 2024 | | 2024 |
An -No-Regret Algorithm For Graphical Bilinear Bandits G Rizk, I Colin, A Thomas, R Laraki, Y Chevaleyre Advances in Neural Information Processing Systems 35, 19113-19123, 2022 | | 2022 |
Differentially Private Deep Model-Based Reinforcement Learning A Rio, M Barlier, I Colin, A Thomas Seventeenth European Workshop on Reinforcement Learning, 0 | | |
A Study of the Weighted Multi-step Loss Impact on the Predictive Error and the Return in MBRL A Benechehab, A Thomas, G Paolo, M Filippone, B Kégl I Can't Believe It's Not Better Workshop: Failure Modes of Sequential …, 0 | | |
Fair Model-Based Reinforcement Learning Comparisons with Explicit and Consistent Update Frequency A Thomas, A Benechehab, G Paolo, B Kégl The Third Blogpost Track at ICLR 2024, 0 | | |